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Electrophysiological Biomarkers of Epileptogenicity in Alzheimer’s Disease

Cortical network hyperexcitability is an inextricable feature of Alzheimer’s disease (AD) that also might accelerate its progression. Seizures are reported in 10–22% of patients with AD, and subclinical epileptiform abnormalities have been identified in 21–42% of patients with AD without seizures. A...

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Autores principales: Yu, Tingting, Liu, Xiao, Wu, Jianping, Wang, Qun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8669481/
https://www.ncbi.nlm.nih.gov/pubmed/34916917
http://dx.doi.org/10.3389/fnhum.2021.747077
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author Yu, Tingting
Liu, Xiao
Wu, Jianping
Wang, Qun
author_facet Yu, Tingting
Liu, Xiao
Wu, Jianping
Wang, Qun
author_sort Yu, Tingting
collection PubMed
description Cortical network hyperexcitability is an inextricable feature of Alzheimer’s disease (AD) that also might accelerate its progression. Seizures are reported in 10–22% of patients with AD, and subclinical epileptiform abnormalities have been identified in 21–42% of patients with AD without seizures. Accurate identification of hyperexcitability and appropriate intervention to slow the compromise of cognitive functions of AD might open up a new approach to treatment. Based on the results of several studies, epileptiform discharges, especially those with specific features (including high frequency, robust morphology, right temporal location, and occurrence during awake or rapid eye movement states), frequent small sharp spikes (SSSs), temporal intermittent rhythmic delta activities (TIRDAs), and paroxysmal slow wave events (PSWEs) recorded in long-term scalp electroencephalogram (EEG) provide sufficient sensitivity and specificity in detecting cortical network hyperexcitability and epileptogenicity of AD. In addition, magnetoencephalogram (MEG), foramen ovale (FO) electrodes, and computational approaches help to find subclinical seizures that are invisible on scalp EEGs. We performed a comprehensive analysis of the aforementioned electrophysiological biomarkers of AD-related seizures.
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spelling pubmed-86694812021-12-15 Electrophysiological Biomarkers of Epileptogenicity in Alzheimer’s Disease Yu, Tingting Liu, Xiao Wu, Jianping Wang, Qun Front Hum Neurosci Neuroscience Cortical network hyperexcitability is an inextricable feature of Alzheimer’s disease (AD) that also might accelerate its progression. Seizures are reported in 10–22% of patients with AD, and subclinical epileptiform abnormalities have been identified in 21–42% of patients with AD without seizures. Accurate identification of hyperexcitability and appropriate intervention to slow the compromise of cognitive functions of AD might open up a new approach to treatment. Based on the results of several studies, epileptiform discharges, especially those with specific features (including high frequency, robust morphology, right temporal location, and occurrence during awake or rapid eye movement states), frequent small sharp spikes (SSSs), temporal intermittent rhythmic delta activities (TIRDAs), and paroxysmal slow wave events (PSWEs) recorded in long-term scalp electroencephalogram (EEG) provide sufficient sensitivity and specificity in detecting cortical network hyperexcitability and epileptogenicity of AD. In addition, magnetoencephalogram (MEG), foramen ovale (FO) electrodes, and computational approaches help to find subclinical seizures that are invisible on scalp EEGs. We performed a comprehensive analysis of the aforementioned electrophysiological biomarkers of AD-related seizures. Frontiers Media S.A. 2021-11-30 /pmc/articles/PMC8669481/ /pubmed/34916917 http://dx.doi.org/10.3389/fnhum.2021.747077 Text en Copyright © 2021 Yu, Liu, Wu and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Yu, Tingting
Liu, Xiao
Wu, Jianping
Wang, Qun
Electrophysiological Biomarkers of Epileptogenicity in Alzheimer’s Disease
title Electrophysiological Biomarkers of Epileptogenicity in Alzheimer’s Disease
title_full Electrophysiological Biomarkers of Epileptogenicity in Alzheimer’s Disease
title_fullStr Electrophysiological Biomarkers of Epileptogenicity in Alzheimer’s Disease
title_full_unstemmed Electrophysiological Biomarkers of Epileptogenicity in Alzheimer’s Disease
title_short Electrophysiological Biomarkers of Epileptogenicity in Alzheimer’s Disease
title_sort electrophysiological biomarkers of epileptogenicity in alzheimer’s disease
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8669481/
https://www.ncbi.nlm.nih.gov/pubmed/34916917
http://dx.doi.org/10.3389/fnhum.2021.747077
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